# TranscriptFetch MCP Server A [Model Context Protocol](https://modelcontextprotocol.io) server that gives any MCP client (Claude Desktop, Cursor, and others) access to the [TranscriptFetch API](https://transcriptfetch.com): a production transcript API for YouTube, TikTok and Instagram, with AI transcription when captions are missing. Fetch transcripts, search videos, list channels and playlists, and check your credit balance. ## Get an API key 1. Create a free account at [transcriptfetch.com](https://transcriptfetch.com/sign-up). No card needed. 2. Open [Dashboard, then API keys](https://transcriptfetch.com/app/keys) and create a key. It starts with `tf_live_`. 3. Put it in `TRANSCRIPTFETCH_API_KEY` in the client configuration below. Every account gets 50 free credits a month. Failures are free: a fetch that returns no transcript is never charged. Runs locally over stdio and calls the TranscriptFetch API with your key. Prefer a hosted, remote server? Point your client at `https://transcriptfetch.com/mcp` instead (OAuth or API key). The hosted server waits inline for short-form AI transcription, so no polling is needed there. ## Tools | Tool | What it does | |---|---| | `get_transcript` | Transcript for a video. YouTube, TikTok, Instagram, or a direct media URL. Set `ai_fallback: true` to transcribe the audio when no captions exist (typically ~30 seconds for short videos, longer for long ones) | | `search_videos` | Search YouTube by keyword | | `list_channel_videos` | List a YouTube channel's videos (handle, ID, or URL) | | `list_playlist_videos` | List a YouTube playlist's videos (ID or URL) | | `get_credits` | Remaining credit balance for the key. Never billed | Pricing is per successful result: a caption fetch or a video list costs 1 credit, and AI transcription of the audio costs 1 credit per started 5 minutes of audio, charged only on delivery. Failed, blocked and empty results are never charged, which matters on short-form video where many clips have no speech at all. ## Install No install needed. Run it on demand with `npx`: ```bash TRANSCRIPTFETCH_API_KEY=tf_live_... npx -y transcriptfetch-mcp ``` Or install globally: ```bash npm install -g transcriptfetch-mcp ``` Requires Node 18+. ### Run from source ```bash git clone https://github.com/TranscriptFetch/mcp-server cd mcp-server && npm install && npm run build ``` Then point your client at the built entrypoint with `"command": "node"` and `"args": ["/absolute/path/to/mcp-server/dist/index.js"]`. ## Client configuration ### Claude Desktop Add this to `claude_desktop_config.json` (Settings then Developer then Edit Config): ```json { "mcpServers": { "transcriptfetch": { "command": "npx", "args": ["-y", "transcriptfetch-mcp"], "env": { "TRANSCRIPTFETCH_API_KEY": "tf_live_..." } } } } ``` ### Cursor Add the same block under `mcpServers` in your Cursor MCP settings. Restart the client, and the five tools appear. ## Example Once connected, ask your assistant naturally: > Get the transcript for https://youtu.be/aircAruvnKk and summarize the key points. > Search YouTube for "how transformers work" and list the top 5 videos. > List the latest videos from @lexfridman and pull the transcript of the newest one. > How many TranscriptFetch credits do I have left? The assistant picks the matching tool and works from the returned transcript or video list. ## Configuration | Env var | Required | Default | |---|---|---| | `TRANSCRIPTFETCH_API_KEY` | yes | none | | `TRANSCRIPTFETCH_BASE_URL` | no | `https://transcriptfetch.com` | ## Docker The server speaks MCP over stdio, so there is no port to expose. `-i` is required: without an attached stdin the transport closes immediately and the container looks like it crashed. ```bash docker build -t transcriptfetch-mcp . docker run --rm -i -e TRANSCRIPTFETCH_API_KEY=tf_live_... transcriptfetch-mcp ``` ## Links - API docs: https://transcriptfetch.com/docs - MCP docs: https://transcriptfetch.com/docs/mcp - Node SDK: https://github.com/TranscriptFetch/transcript-api-node - Python SDK: https://github.com/TranscriptFetch/transcript-api-python ## License MIT